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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/67791

    Título
    Pre-fire aboveground biomass, estimated from LiDAR, spectral and field inventory data, as a major driver of burn severity in maritime pine (Pinus pinaster) ecosystems
    Autor
    Fernández Guisuraga, José Manuel
    Suárez Seoane, Susana
    Fernandes, Paolo
    Fernández García, Victor
    Fernández Manso, Alfonso
    Quintano Pastor, María del CarmenAutoridad UVA Orcid
    Calvo, Leonor
    Año del Documento
    2022
    Editorial
    Elsevier
    Descripción
    Producción Científica
    Documento Fuente
    Forest Ecosystems, Febrero 2022, 9, 100022.
    Résumé
    Background: The characterization of surface and canopy fuel loadings in fire-prone pine ecosystems is critical for understanding fire behavior and anticipating the most harmful ecological effects of fire. Nevertheless, the joint consideration of both overstory and understory strata in burn severity assessments is often dismissed. The aim of this work was to assess the role of total, overstory and understory pre-fire aboveground biomass (AGB), estimated by means of airborne Light Detection and Ranging (LiDAR) and Landsat data, as drivers of burn severity in a megafire occurred in a pine ecosystem dominated by Pinus pinaster Ait. in the western Mediterranean Basin. Results: Total and overstory AGB were more accurately estimated (R2 equal to 0.72 and 0.68, respectively) from LiDAR and spectral data than understory AGB (R2 ¼ 0.26). Density and height percentile LiDAR metrics for several strata were found to be important predictors of AGB. Burn severity responded markedly and non-linearly to total (R2 ¼ 0.60) and overstory (R2 ¼ 0.53) AGB, whereas the relationship with understory AGB was weaker (R2 ¼ 0.21). Nevertheless, the overstory plus understory AGB contribution led to the highest ability to predict burn severity (RMSE ¼ 122.46 in dNBR scale), instead of the joint consideration as total AGB (RMSE ¼ 158.41). Conclusions: This study novelty evaluated the potential of pre-fire AGB, as a vegetation biophysical property derived from LiDAR, spectral and field plot inventory data, for predicting burn severity, separating the contribution of the fuel loads in the understory and overstory strata in Pinus pinaster stands. The evidenced relationships between burn severity and pre-fire AGB distribution in Pinus pinaster stands would allow the implementation of threshold criteria to support decision making in fuel treatments designed to minimize crown fire hazard.
    Palabras Clave
    Aboveground biomass
    Burn severity
    Landsat
    LiDAR
    Pinus pinaster
    Revisión por pares
    SI
    DOI
    10.1016/j.fecs.2022.100022
    Patrocinador
    Spanish Ministry of Economy and Competitiveness, and the European Regional Development Fund (ERDF), GESFIRE project (AGL2013-48189-C2-1-R);
    Spanish Ministry of Economy and Competitiveness, and the European Regional Development Fund (ERDF), iFIRESEVES project (AGL2017-86075-C2-1-R)
    Regional Government of Castilla and Leon FIRECYL project (LE033U14)
    Regional Government of Castilla and Leon SEFIRECYL project (LE001P17)
    Regional Government of Castilla and Leon, WUIFIRECYL project (LE005P20)
    Version del Editor
    https://www.sciencedirect.com/science/article/pii/S2197562022000227
    Propietario de los Derechos
    Elsevier
    Idioma
    spa
    URI
    https://uvadoc.uva.es/handle/10324/67791
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
    Aparece en las colecciones
    • DEP69 - Artículos de revista [32]
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    2022_FE_Pre-fire_aboveground_biomass.pdf
    Tamaño:
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